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Record W2906701517 · doi:10.1063/1.5062156

Investigation of near-wall turbulence in relation to polymer rheology

2018· article· en· W2906701517 on OpenAlex
Sadek M Ali Shaban, Madhar Sahib Azad, Japan Trivedi, Sina Ghaemi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysics of Fluids · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWeissenberg numberTurbulenceDragRheologyPhysicsBoundary layerShear thinningShear ratePolymerNewtonian fluidMechanicsThermodynamicsOpticsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

An experimental investigation was carried out to characterize the rheology of polyacrylamide solutions and its effect on the structure of a turbulent channel flow. The shear viscosity of 10 and 20 ppm solutions had similar magnitudes as that of water with a Newtonian behavior, while the 90 and 160 ppm solutions had a shear-thinning behavior. The elasticity and relaxation time of the solutions monotonously increased with an increase in polymer concentration. Pressure drop measurement at a Reynold number of 20 000 showed 25, 43, 51, and 57% drag reduction for 10, 20, 90, and 160 ppm solutions, respectively. Time-resolved planar particle image velocimetry was used to characterize the turbulent structure. The polymers were more effective in reducing the strain-rate in the buffer layer due to the larger strain rate and stretching of the polymers. This was consistent with larger values of the Weissenberg number in the buffer layer compared with the log layer. The distributions of the Weissenberg number showed two distinct distributions at the low and high drag reduction regimes. The addition of the polymers to the turbulent flow was observed to balance the local strain rate and rotation. This effect was observed in the inner layer for all polymer concentrations, while it was observed in the logarithmic layer only for the 90 and 160 ppm solutions. The power spectral density of turbulence kinetic energy in the buffer layer showed that the high frequency content was damped for the 10 and 20 ppm solutions, while a wider frequency range was attenuated at a higher polymer concentration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.235
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it